ANTI-DSDNA ANTIBODY ISOTYPES IN SYSTEMIC LUPUS ERYTHEMATOSUS: THE NEGLECTED DIAGNOSTIC PARAMETERS
Bibliographic record
Abstract
PV038 / #485 Poster Topic: AS04 - Biomarkers Background/Purpose In systemic lupus erythematosus (SLE) many different organs are affected by an immune response including the skin, blood, muscles, heart, lung or kidneys making the range of symptoms vary widely. SLE occurs in about 0.1% of the general population and is predominant in females, especially in the age between 20 and 40 years, and may be linked to the hormone estrogen. Anti-double-stranded DNA (dsDNA) antibodies are highly specific for the disease and can be found in 30-40% of patients. Perform a comprehensive literature search to identify all relevant available published data for demonstration of the State-of-the-Art (medicine and technology, SOTA), the Scientific Validity (SV) of the analyte and the Clinical Performance (CP) of anti-dsDNA autoantibodies. Methods Systematic literature search, evaluation and documentation was done by applying PRISMA method. The search strings are assembled with the use of Boolean operators and search was restricted to peer-reviewed literature and systematic reviews. Results In total 22 publications have been identified as significant for SOTA, SV and CP of anti-dsDNA antibodies. The reviewed literature concludes that anti-dsDNA antibodies are specific and pathogenic biomarkers for monitoring SLE. IgG anti-dsDNA antibodies are the gold standard for diagnosing and monitoring SLE, especially in patients with kidney involvement (lupus nephritis) being the most common and severe organ manifestation. These antibodies can bind to self-antigens or immune complexes and accumulate in the glomerular and tubular basement membranes. Defective clearance of apoptotic cells may trigger the production of anti-dsDNA antibodies. Anti-dsDNA IgA and IgG show a strong association with disease activity, and the IgA isotype is additionally associated with several symptoms of skin involvement. However, the IgA isotype has no association with nephritis and arthritis and may therefore define a distinct subset of SLE patients. The presence of IgM anti-dsDNA antibodies shows a negative correlation with various parameters indicating lupus nephritis. Due to the contrary roles of IgG and IgM anti-dsDNA Isotypes in the pathogenesis of Lupus Nephritis, there is strong scientific evidence to use the IgG/ IgM Isotype ratio for prediction of nephritis (IgG/IgM >0.8 nephritis; IgG/IgM <0.8 no nephritis) also considered as replacement for kidney biopsy. Anti-dsDNA isotype evaluation in ELISA might indeed improve diagnostic accuracy, and multiple isotype detection (IgG, IgA, IgM) could enhance sensitivity in detecting the disease. Conclusions Almost all patients with renal problems show anti-dsDNA antibodies and they are also suitable for disease monitoring, since anti-dsDNA antibody concentration increases before disease flares but there is still some controversy. But even though anti-dsDNA antibodies have been established as one of the American College of Rheumatology (ACR) and Systemic Lupus International Collaborating Clinics’ criteria for diagnosing SLE, IgA and IgM anti-dsDNA isotypes are not included in follow-up routine of the patients. The combination of analysis of different anti-dsDNA isotypes (IgG, IgA, IgM) provides a more nuanced perspective on SLE disease. It not only enables more precise diagnosis, but also better monitoring of disease activity and progression, especially when distinguishing between organ involvement and tracking treatment courses. Overall, the analysis of anti-dsDNA antibody isotypes could provide a tailored and more precise diagnostic strategy in clinical practice, which may be particularly important in the monitoring of lupus nephritis and the specific treatment of SLE patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".